# How to Filter a List of Lists in Python?

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Short answer: To filter a list of lists for a condition on the inner lists, use the list comprehension statement `[x for x in list if condition(x)]` and replace `condition(x)` with your filtering condition that returns `True` to include inner list `x`, and `False` otherwise.

Lists belong to the most important data structures in Python—every master coder knows them by heart! Surprisingly, even intermediate coders don’t know the best way to filter a list—let alone a list of lists in Python. This tutorial shows you how to do the latter!

Problem: Say, you’ve got a list of lists. You want to filter the list of lists so that only those inner lists remain that satisfy a certain condition. The condition is a function of the inner list—such as the average or sum of the inner list elements.

Example: Given the following list of lists with weekly temperature measurements per week—and one inner list per week.

```# Measurements of a temperature sensor (7 per week)
temperature = [[10, 8, 9, 12, 13, 7, 8], # week 1
[9, 9, 5, 6, 6, 9, 11], # week 2
[10, 8, 8, 5, 6, 3, 1]] # week 3```

How to filter out the colder weeks with average temperature value <8? This is the output you desire:

```print(cold_weeks)
# [[9, 9, 5, 6, 6, 9, 11], [10, 8, 8, 5, 6, 3, 1]]```

There are two semantically equivalent methods to achieve this: list comprehension and the `map()` function. Let’s explore both variants next.

If you’re short on time, you can also get a quick overview by playing with the code in your web browser—I’ll explain the code after that.

## Method 1: List Comprehension

The most Pythonic way of filtering a list—in my opinion—is the list comprehension statement `[x for x in list if condition]`. You can replace `condition` with any function of `x` you would like to use as a filtering condition. Only elements that are in the `list` and meet the `condition` are included in the newly created list.

Solution: Here’s how you can solve the above problem to filter a list of lists based on a function of the inner lists:

```# Measurements of a temperature sensor (7 per week)
temperature = [[10, 8, 9, 12, 13, 7, 8], # week 1
[9, 9, 5, 6, 6, 9, 11], # week 2
[10, 8, 8, 5, 6, 3, 1]] # week 3

# How to filter weeks with average temperature <8?

# Method 1: List Comprehension
cold_weeks = [x for x in temperature if sum(x)/len(x)<8]
print(cold_weeks)
# [[9, 9, 5, 6, 6, 9, 11], [10, 8, 8, 5, 6, 3, 1]]```

The second and third list in the list of lists meet the condition of having an average temperature of less than 8 degrees. So those are included in the variable `cold_weeks`.

You can visualize the memory usage of this code snippet in the following interactive tool:

This is the most efficient way of filtering a list and it’s also the most Pythonic one. If you look for alternatives though, keep reading.

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## Method 2: Filter() Function

The `filter(function, iterable)` function takes a function as input that takes on argument (a list element) and returns a Boolean value that indicates whether this list element should pass the filter. All elements that pass the filter are returned as a new `iterable` object (a filter object).

You can use the `lambda` function statement to create the function right where you pass it as an argument. The syntax of the lambda function is `lambda x: expression` and it means that you use `x` as an input argument and you return expression as a result (that can or cannot use `x` to decide about the return value). For more information, see my detailed blog article about the lambda function.

```# Measurements of a temperature sensor (7 per week)
temperature = [[10, 8, 9, 12, 13, 7, 8], # week 1
[9, 9, 5, 6, 6, 9, 11], # week 2
[10, 8, 8, 5, 6, 3, 1]] # week 3

# How to filter weeks with average temperature <8?

# Method 2: Map()
cold_weeks = list(filter(lambda x: sum(x) / len(x) < 8, temperature))
print(cold_weeks)
# [[9, 9, 5, 6, 6, 9, 11], [10, 8, 8, 5, 6, 3, 1]]```

Again, the second and third list in the list of lists meet the condition of having an average temperature of less than 8 degrees. So those are included in the variable `cold_weeks`.

The `filter()` function returns a filter object that’s an `iterable`. To convert it to a list, you use the `list(...)` constructor.

Play with this code by clicking “Next” in the interactive code visualization tool:

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## Where to Go From Here?

Enough theory. Let’s get some practice!

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You build high-value coding skills by working on practical coding projects!

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🚀 If your answer is YES!, consider becoming a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.

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